Predictor of respiratory disturbances during gastric endoscopic submucosal dissection under deep sedation.

Abstract

BACKGROUNDSedation is commonly performed for the endoscopic submucosal dissection (ESD) of early gastric cancer. Severe hypoxemia occasionally occurs due to the respiratory depression during sedation.AIMTo establish predictive models for respiratory depression during sedation for ESD.METHODSThirty-five adult patients undergoing sedation using propofol and pentazocine for gastric ESDs participated in this prospective observational study. Preoperatively, a portable sleep monitor and STOP questionnaires, which are the established screening tools for sleep apnea syndrome, were utilized. Respiration during sedation was assessed by a standard polysomnography technique including the pulse oximeter, nasal pressure sensor, nasal thermistor sensor, and chest and abdominal respiratory motion sensors. The apnea-hypopnea index (AHI) was obtained using a preoperative portable sleep monitor and polysomnography during ESD. A predictive model for the AHI during sedation was developed using either the preoperative AHI or STOP questionnaire score.RESULTSAll ESDs were completed successfully and without complications. Seventeen patients (49%) had a preoperative AHI greater than 5/h. The intraoperative AHI was significantly greater than the preoperative AHI (12.8 ± 7.6 events/h vs 9.35 ± 11.0 events/h, P = 0.049). Among the potential predictive variables, age, body mass index, STOP questionnaire score, and preoperative AHI were significantly correlated with AHI during sedation. Multiple linear regression analysis determined either STOP questionnaire score or preoperative AHI as independent predictors for intraoperative AHI ≥ 30/h (area under the curve [AUC]: 0.707 and 0.833, respectively) and AHI between 15 and 30/h (AUC: 0.761 and 0.778, respectively).CONCLUSIONThe cost-effective STOP questionnaire shows performance for predicting abnormal breathing during sedation for ESD that was equivalent to that of preoperative portable sleep monitoring.